With the development of improved three-dimensional (3D) projection technologies, as used in theatres, amusement rides, etc., and the more recent introduction of 3D television sets, the demand for 3D image content is rapidly increasing. Accordingly, there has been considerable interest in converting 2D images (e.g., feature length movies, television shows, etc.) captured using mono-view devices into 3D images.
Some of the conventional mono-view 2D-to-3D conversion techniques utilize computer vision based technologies, such as segmentation, vanishing line detection, etc. Likewise, some mono-view 2D-to-3D conversion techniques utilize motion information, such as to capture content obscured by an object moving in the foreground. These technologies, however, are generally not practical for real time 2D-to-3D conversion. In particular, such computer vision based technologies require significant computing resources and are not well suited either for real time operation or for low cost applications.
Other techniques used to convert 2D images to 3D images generate a depth map (i.e., an image or image channel that contains information relating to the distance of the surfaces of scene objects from a viewpoint), then use the depth map to create the left and right view (i.e., parallax views) from the image in accordance with the depth map. For example, various techniques utilize a global depth model and more localized depth analysis to generate a local depth map with which a 3D image may be generated. The global depth model provides a generalized depth model for the image, such as may be based on a planar model or spherical model, which does not accurately reflect the local depth discontinuity. Accordingly, more localized analysis, such as image texture analysis, is used with the global depth model to generate a local depth map for the image which more accurately reflects the local depth discontinuity.
The image depth maps generated using the foregoing global depth model and localized depth analysis techniques are often less than ideal, such as due to the use of the global depth models not dynamically representing the images to be converted and the localized depth analysis techniques used not accurately representing local depth. For example, a global depth model chosen as a central symmetric model may be used by scene analysis, wherein the model will keep central symmetry for all the frames of the scene irrespective of changes within the scene (e.g., movement or motion not rising to the level of a scene change). Likewise, local depth assignments made using typical localized depth analysis techniques are particularly inaccurate under poor light conditions.